systems, apparatuses and methods may provide for technology to improve a workout experience of a user by determining an emotional state of the user, identifying a workout route based on the emotional state of the user, and outputting the workout route via a user interface device. Additionally, determining the emotional state of the user may include inferring emotions from one or more sensor information or user speech information. In one example, the sensor information includes one or more of blood pressure signals, heart rate signals or sweat measurement signals and the user speech information includes one or more of words used in an input utterance or a prosody of the input utterance.
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13. A method comprising:
determining, via an emotion monitor, an emotional state of a user, wherein the emotion monitor is to infer emotions from one or more of sensor information or user speech information;
identifying a workout route based on the emotional state of the user, wherein identifying the workout rout includes identifying a relaxing workout route when the user is stressed, a regular workout route when the user is happy, and a new workout route when the user is bored; and
outputting the workout route via a user interface device.
5. An apparatus comprising:
an emotion monitor to determine an emotional state of a user, wherein the emotion monitor is to infer emotions from one or more of sensor information or user speech information;
a route selector communicatively coupled to the emotion monitor, the route selector to identify a workout route based on the emotional state of the user, wherein the route selector is to identify a relaxing workout route when the user is stressed, a regular workout route when the user is happy, and a new workout route when the user is bored; and
a notifier communicatively coupled to the route selector, the notifier to output the workout route via a user interface device.
17. At least one non-transitory computer readable storage medium comprising a set of instructions which, if executed by a computing device, cause the computing device to:
determine, via an emotion monitor, an emotional state of a user, wherein the emotion monitor is to infer emotions from one or more of sensor information or user speech information;
identify a workout route based on the emotional state of the user, wherein to identify the workout route, the instructions, when executed, cause the computing device to identify a relaxing workout route when the user is stressed, a regular workout route when the user is happy, and a new workout route when the user is bored; and
output the workout route via a user interface device.
1. A system comprising:
a housing having a wearable form factor;
a processor;
memory communicatively coupled to the processor;
a user interface device communicatively coupled to the processor; and
an emotional workout apparatus communicatively coupled to the processor, the emotional workout apparatus including:
an emotion monitor to determine an emotional state of a user, wherein the emotion monitor is to infer emotions from one or more of sensor information or user speech information;
a route selector communicatively coupled to the emotion monitor, the route selector to identify a workout route based on the emotional state of the user, wherein the route selector is to identify a relaxing workout route when the user is stressed, a regular workout route when the user is happy, and a new workout route when the user is bored; and
a notifier communicatively coupled to the route selector, the notifier to output the workout route via the user interface device.
2. The system of
3. The system of
4. The system of
6. The apparatus of
7. The apparatus of
8. The apparatus of
9. The apparatus of
10. The apparatus of
11. The apparatus of
12. The apparatus of
14. The method of
15. The method of
16. The method of
18. The at least one non-transitory computer readable storage medium of
19. The at least one non-transitory computer readable storage medium of
20. The at least one non-transitory computer readable storage medium of
21. The at least one non-transitory computer readable storage medium of
identify one or more routes in the list that have been previously followed by the user; and
prevent the one or more routes from being identified as the workout route.
22. The at least one non-transitory computer readable storage medium of
23. The at least one non-transitory computer readable storage medium of
24. The at least one non-transitory computer readable storage medium of
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The present application is a continuation of and claims the benefit of priority to U.S. Non-Provisional patent application Ser. No. 15/396,243 filed on Dec. 30, 2016.
Embodiments generally relate to workout technology. More particularly, embodiments relate to using emotional maps and dialog systems to improve workout experiences.
Workouts for runners and cyclists may rely heavily on the physical distribution of the area where the athlete is training. For any given workout session, the athlete may perform it along a route that has a certain distance, provides a target level of difficulty and is feasible in terms of traffic, etc.
Automated coaching dialogue systems (e.g., software running in a smartphone with a dialogue system trained as a coach) may define workout plans but rely on the athlete/sportsman to choose the best route to apply. The dialogue systems may also give directions on the general characteristics of the workout for that day and let the athlete find the route that is suitable for his or her workout. While these systems may be suitable under certain circumstances, there remains considerable room for improvement.
The various advantages of the embodiments will become apparent to one skilled in the art by reading the following specification and appended claims, and by referencing the following drawings, in which:
For example, computer program code to carry out operations shown in method 201 may be written in any combination of one or more programming languages, including an object-oriented programming language such as C#, JAVA or the like. Additionally, logic instructions might include assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, state-setting data, configuration data for integrated circuitry, state information that personalizes electronic circuitry and/or other structural components that are native to hardware (e.g., host processor, central processing unit/CPU, microcontroller, etc.).
Illustrated processing block 202 starts operation of the automated coaching system. In illustrated processing block 204, the system determines an emotional state of a user (e.g., stressed, happy, sad, bored, etc.). Determining the emotional state of the user may include, for example, inferring emotions from one or more of sensor information or user speech information. The sensor information may include, for example, blood pressure signals, heart rate signals, sweat measurement signals, etc., or any combination thereof. The user speech information might include, for example, words used in an input utterance, a prosody of the input utterance, etc., or any combination thereof.
Based on the emotional state of the user, block 206 may identify a workout route. In illustrated processing block 208, the apparatus may output the workout route via a user interface (UI) device, wherein the user interface device may include a display, speaker(s), vibration subsystem (e.g., haptic motor), printer, or other wearable/fitness UI device.
In illustrated processing block 210, if the coaching system determines that there is change in the emotional state of the user, the system automatically updates the emotional state of the user in illustrated processing block 204. If there is no change in the emotional state of the user, the coaching system may terminate the method 201 in illustrated processing block 212.
Another example of dynamic update may arise from the user deviating from the predefined route. In such a case, the system may ask why the user decided to do so, and update emotional map information accordingly. For instance, the user may answer that she found the route very noisy and the system could add this piece of information to an emotional map database, as will be discussed in greater detail.
In illustrated processing block 302, the coaching system creates a list of previously stored routes for one or more tags. The tags may be generated by the coaching system from previously used keywords. Examples tags might include, for example, landscape, traffic, noise, etc., or any combination thereof. In illustrated processing block 304, the coaching system searches the list of previously stored roads for one or more tags associated with the emotional state of the user. When searching the list of previously stored routes, the system may prompt the user for specific routes in which the user is interested. For example, block 304 may determine that the user is interested in a quiet and pleasant route, a route with natural landscapes, a tourist route, etc.
In illustrated processing block 306, the automated coaching system, in response to searching the list of previously stored roads by the user, identifies one or more routes in the list that were previously followed. Block 306 may use historical information stored in local memory or retrieved from a remote source (e.g., server, cloud computing infrastructure). In illustrated processing block 308, the automated coach apparatus prevents the one or more previously followed routes form being identified as the workout route. Thus, by ensuring that the user does not repeat the same path to a point of boredom, block 308 may increase the likelihood that long-term fitness goals are achieved.
An example of the impact of the illustrated processing block 308 is the following: the user might ask to perform a cycling workout through a touristic route, wherein the community may rank a given path as the most interesting one from a touristic point of view. The illustrated solution may suggest, however, a different route because the highly-ranked route was followed by the user in a previous workout.
The emotional information may therefore work in two ways:
From the route's point of view in which potential routes are pre-classified as “emotional maps” following the feedback provided by other users. The system may have a set of alternatives ranked according to several “emotional” criteria (pleasantness, beauty, etc.). Since the criteria are subjective, the ranking may be based on the average of the user feedback.
From the user's point of view in which the system is able to determine what sort of route the user is interested in at any given time. For instance, after a stressful day of work, the user may say “I want to do my workout in a quiet route, please” or the system may automatically detect that the user is stressed based on sensor data.
The system may use the accumulated information when planning the workout and adapt to the preferences of the user. The route may also be updated in real-time during the workout. The update may be conducted as a result of a direct request from the user (e.g., “I would like to change to a more beautiful route”), an indirect observation (“This route is really ugly”), an inferred emotional from sensor data, etc., or any combination thereof.
As already noted, the route may also be updated without even an indirect input from the user. For example, the system may decide to do so based on the output of a sentiment analysis module (e.g., sentiment analyzer). For instance, the sentiment analysis module may point to a high level of stress in the athlete, making the system decide to select a more relaxing route. Alternatively, the sentiment analysis module may point to a sad mood, making the system suggest a livelier path.
The sentiment analysis module may automatically develop conclusions from inputs such as the words chosen by the user or the prosody of captured speech. Also, in the specific fitness context at hand, other sources of information may be used such as, for example, the type of music selected for the workout (if any), sensor information (heart-rate, sweat, etc.), and so forth.
Another example of a dynamic update may arise from the user deviating from the predefined route. As already noted, the system may ask the user why he or she decided to do so, and update the emotional map information accordingly. For instance, the user may answer that she found the route very noisy and the system could add this piece of information to the emotional map database.
Another emotional factor that the system may take into account is boredom. It may be important for the long-term success of a training plan that the user sticks to the plan until its end, so avoiding boredom may be particularly advantageous. The technology described herein may prevent this risk by taking historical information into account.
Weight=F (Source, History).
The processor core 200 is shown including execution logic 250 having a set of execution units 255-1 through 255-N. Some embodiments may include a number of execution units dedicated to specific functions or sets of functions. Other embodiments may include only one execution unit or one execution unit that can perform a particular function. The illustrated execution logic 250 performs the operations specified by code instructions.
After completion of execution of the operations specified by the code instructions, back end logic 260 retires the instructions of the code 213. In one embodiment, the processor core 200 allows out of order execution but requires in order retirement of instructions. Retirement logic 265 may take a variety of forms as known to those of skill in the art (e.g., re-order buffers or the like). In this manner, the processor core 200 is transformed during execution of the code 213, at least in terms of the output generated by the decoder, the hardware registers and tables utilized by the register renaming logic 225, and any registers (not shown) modified by the execution logic 250.
Although not illustrated in
Referring now to
The system 1000 is illustrated as a point-to-point interconnect system, wherein the first processing element 1070 and the second processing element 1080 are coupled via a point-to-point interconnect 1050. It should be understood that any or all of the interconnects illustrated in
As shown in
Each processing element 1070, 1080 may include at least one shared cache 1896a, 1896b (e.g., static random access memory/SRAM). The shared cache 1896a, 1896b may store data (e.g., objects, instructions) that are utilized by one or more components of the processor, such as the cores 1074a, 1074b and 1084a, 1084b, respectively. For example, the shared cache 1896a, 1896b may locally cache data stored in a memory 1032, 1034 for faster access by components of the processor. In one or more embodiments, the shared cache 1896a, 1896b may include one or more mid-level caches, such as level 2 (L2), level 3 (L3), level 4 (L4), or other levels of cache, a last level cache (LLC), and/or combinations thereof.
While shown with only two processing elements 1070, 1080, it is to be understood that the scope of the embodiments are not so limited. In other embodiments, one or more additional processing elements may be present in a given processor. Alternatively, one or more of processing elements 1070, 1080 may be an element other than a processor, such as an accelerator or a field programmable gate array. For example, additional processing element(s) may include additional processors(s) that are the same as a first processor 1070, additional processor(s) that are heterogeneous or asymmetric to processor a first processor 1070, accelerators (such as, e.g., graphics accelerators or digital signal processing (DSP) units), field programmable gate arrays, or any other processing element. There can be a variety of differences between the processing elements 1070, 1080 in terms of a spectrum of metrics of merit including architectural, micro architectural, thermal, power consumption characteristics, and the like. These differences may effectively manifest themselves as asymmetry and heterogeneity amongst the processing elements 1070, 1080. For at least one embodiment, the various processing elements 1070, 1080 may reside in the same die package.
The first processing element 1070 may further include memory controller logic (MC) 1072 and point-to-point (P-P) interfaces 1076 and 1078. Similarly, the second processing element 1080 may include a MC 1082 and P-P interfaces 1086 and 1088. As shown in
The first processing element 1070 and the second processing element 1080 may be coupled to an I/O subsystem 1090 via P-P interconnects 1076 1086, respectively. As shown in
In turn, I/O subsystem 1090 may be coupled to a first bus 1016 via an interface 1096. In one embodiment, the first bus 1016 may be a Peripheral Component Interconnect (PCI) bus, or a bus such as a PCI Express bus or another third generation I/O interconnect bus, although the scope of the embodiments are not so limited.
As shown in
Note that other embodiments are contemplated. For example, instead of the point-to-point architecture of
Example 1 may include a system to improve workout experiences, comprising a housing having a wearable form factor, a user interface device, and an emotion monitor to determine an emotional state of a user, a route selector communicatively coupled to the emotion monitor, the route selector to identify a workout route based on the emotional state of the user; and a notifier communicatively coupled to the route selector, the notifier to output the workout route via the user interface device.
Example 2 may include the system of Example 1, wherein the emotional monitor to determine the emotional state of the user further includes inferring emotions from one or more of sensor information or user speech information, wherein the sensor information includes one or more of blood pressure signals, heart rate signals or sweat measurement signals, and wherein the user speech information includes one or more of words used in an input utterance or a prosody of the input utterance.
Example 3 may include the system of Example 1, wherein the route selector further including updating the workout route during a workout session that implements the workout route based on a change in the emotional state of the user.
Example 4 may include the system of any one of Examples 1 to 3, wherein the route selector further including searching a list of previously stored routes for one or more tags associated with the emotional state of the user.
Example 5 may include an emotional workout apparatus comprising, comprising an emotion monitor to determine an emotional state of a user, a route selector communicatively coupled to the emotion monitor, the route selector to identify a workout route based on the emotional state of the user, and a notifier communicatively coupled to the route selector, the notifier to output the workout route via a user interface device.
Example 6 may include the apparatus of Example 5, wherein the emotional monitor to determine the emotional state of the user further includes to infer emotions from one or more of sensor information or user speech information, wherein the sensor information is to include one or more of blood pressure signals, heart rate signals or sweat measurement signals, and wherein the user speech information is to include one or more of words used in an input utterance or a prosody of the input utterance.
Example 7 may include the apparatus of Example 5, wherein the route selector further including updating the workout route during a workout session that implements the workout route based on a change in the emotional state of the user.
Example 8 may include the apparatus of Example 5, wherein the route selector further includes searching a list of previously stored routes for one or more tags associated with the emotional state of the user.
Example 9 may include the apparatus of Example 8, wherein the road selector further identifies one or more routes in the list that have been previously followed by the user, and prevents the one or more routes from being identified as the workout route.
Example 10 may include the apparatus of Example 8, wherein the road selector further creates the list of previously stored routes based on preconfigured routes and associated tags shared by a plurality of users.
Example 11 may include the apparatus of Example 8, wherein the road selector gives a higher weight to tags shared by the user than tags shared by other users.
Example 12 may include apparatus of any one of Examples 5-11, wherein tags in the list of previously stored routes by the road selector describe factors relevant to an emotional perception of the route.
Example 13 may include a method of operating an emotional workout apparatus, comprising determining an emotional state of a user, identifying a workout route based on the emotional state of the user, and outputting the workout route via a user interface device.
Example 14 may include the method of Example 13, wherein determining the emotional state of the user includes inferring emotions from one or more of sensor information or user speech information, wherein the sensor information includes one or more of blood pressure signals, heart rate signals or sweat measurement signals, and wherein the user speech information includes one or more of words used in an input utterance or a prosody of the input utterance.
Example 15 may include the method of Example 13, further including updating the workout route during a workout session that implements the workout route based on a change in the emotional state of the user.
Example 16 of any one of Example 13-15, further including searching a list of previously stored routes for one or more tags associated with the emotional state of the user.
Example 17 may include at least one non-transitory computer readable storage medium comprising a set of instructions which, if executed by a computing device, cause the computing device to determine an emotional state of a user, identify a workout route based on the emotional state of the user, and output the workout route via a user interface device.
Example 18 may include the at least one non-transitory computer readable storage medium of Example 17, wherein the instructions, if executed, cause a computing device to infer emotions from one or more of sensor information or user speech information, wherein the sensor information is to include one or more of blood pressure signals, heart rate signals or sweat measurement signals, and wherein the user speech information is to include one or more of words used in an input utterance or a prosody of the input utterance.
Example 19 may include the at least one non-transitory computer readable storage medium of Example 17, wherein the instructions, if executed, cause a computing device to update the workout route during a workout session that implements the workout route based on a change in the emotional state of the user.
Example 20 may include the at least one non-transitory computer readable storage medium of Example 17, wherein the instructions, if executed, cause a computing device to search a list of previously stored routes for one or more tags associated with the emotional state of the user.
Example 21 may include the at least one non-transitory computer readable storage medium of Example 20, wherein the instructions, if executed, cause a computing device to identify one or more routes in the list that have been previously followed by the user, and prevent the one or more routes from being identified as the workout route.
Example 22 may include the at least one non-transitory computer readable storage medium of Example 20, wherein the instructions, if executed, cause a computing device to create the list of previously stored routes based on preconfigured routes and associated tags shared by a plurality of users.
Example 23 may include the at least one non-transitory computer readable storage medium of Example 20, wherein the instructions, if executed, cause a computing device to give a higher weight to tags shared by the user than tags shared by other users.
Example 24 may include the at least one non-transitory computer readable storage medium of any of Examples 17-23, wherein tags in the list of previously stored routes describe factors relevant to an emotional perception of the route.
Example 25 may include an emotional workout apparatus, comprising means for determining an emotional state of a user, means for identifying a workout route based on the emotional state of the user, and means for outputting the workout route via a user interface device.
Example 26 may include the apparatus of Example 25, wherein means for determining the emotional state of the user includes inferring emotions from one or more of sensor information or user speech information, wherein the sensor information includes one or more of blood pressure signals, heart rate signals or sweat measurement signals, and wherein the user speech information includes one or more of words used in an input utterance or a prosody of the input utterance.
Example 27 may include the apparatus of Example 25, further including means for updating the workout route during a workout session that implements the workout route based on a change in the emotional state of the user.
Example 28 may include the apparatus of any one of Example 25-27, further including means for searching a list of previously stored routes for one or more tags associated with the emotional state of the user.
Embodiments are applicable for use with all types of semiconductor integrated circuit (“IC”) chips. Examples of these IC chips include but are not limited to processors, controllers, chipset components, programmable logic arrays (PLAs), memory chips, network chips, systems on chip (SoCs), SSD/NAND controller ASICs, and the like. In addition, in some of the drawings, signal conductor lines are represented with lines. Some may be different, to indicate more constituent signal paths, have a number label, to indicate a number of constituent signal paths, and/or have arrows at one or more ends, to indicate primary information flow direction. This, however, should not be construed in a limiting manner. Rather, such added detail may be used in connection with one or more exemplary embodiments to facilitate easier understanding of a circuit. Any represented signal lines, whether or not having additional information, may actually comprise one or more signals that may travel in multiple directions and may be implemented with any suitable type of signal scheme, e.g., digital or analog lines implemented with differential pairs, optical fiber lines, and/or single-ended lines.
Example sizes/models/values/ranges may have been given, although embodiments are not limited to the same. As manufacturing techniques (e.g., photolithography) mature over time, it is expected that devices of smaller size could be manufactured. In addition, well known power/ground connections to IC chips and other components may or may not be shown within the figures, for simplicity of illustration and discussion, and so as not to obscure certain aspects of the embodiments. Further, arrangements may be shown in block diagram form in order to avoid obscuring embodiments, and also in view of the fact that specifics with respect to implementation of such block diagram arrangements are highly dependent upon the platform within which the embodiment is to be implemented, i.e., such specifics should be well within purview of one skilled in the art. Where specific details (e.g., circuits) are set forth in order to describe example embodiments, it should be apparent to one skilled in the art that embodiments can be practiced without, or with variation of, these specific details. The description is thus to be regarded as illustrative instead of limiting.
The term “coupled” may be used herein to refer to any type of relationship, direct or indirect, between the components in question, and may apply to electrical, mechanical, fluid, optical, electromagnetic, electromechanical or other connections. In addition, the terms “first”, “second”, etc. may be used herein only to facilitate discussion, and carry no particular temporal or chronological significance unless otherwise indicated.
As used in this application and in the claims, a list of items joined by the term “one or more of” may mean any combination of the listed terms. For example, the phrases “one or more of A, B or C” may mean A; B; C; A and B; A and C; B and C; or A, B and C.
Those skilled in the art will appreciate from the foregoing description that the broad techniques of the embodiments can be implemented in a variety of forms. Therefore, while the embodiments have been described in connection with particular examples thereof, the true scope of the embodiments should not be so limited since other modifications will become apparent to the skilled practitioner upon a study of the drawings, specification, and following claims.
Perez, Guillermo, Perez Tudela, Israel
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